Engineering the shape memory parameters of graphene/polymer nanocomposites through atomistic simulations: On the effect of nanofiller surface treatment

Abstract

Abstract This paper aims to comprehend the mechanisms underlying the shape memory behavior of polylactic acid infused with graphene functionalized by four groups of –OH, –CH3, –NH2, and tethered polymer layer. Applying molecular dynamics simulation, it is revealed that the graphene surface treatment enhances the shape fixity ratio of nanocomposites monotonically by increasing the physical cross-linking points within the polymer matrix. The improvement would be even more pronounced by increasing the coverage degree of small functional groups and grafting density of the covalently bonded polymer chains. Monitoring the key parameters illustrates that contrary to the OH groups, which improve the shape recovery value, the other functional groups degrade it by prohibiting the polymer chains mobility. Attempts to explore the governing mechanism demonstrate that shape fixity is improved when the difference between the potential energy variations in the loading and unloading stages increases. Interestingly, shape recovery is only under the influence of conformational entropy, and it is not affected by the potential energy. As such, we also probe variations of the radius of gyration during the recovery stage to address the role of different functionalization procedures on the reported shape recovery parameter.